COMPARISON OF ESTIMATED GLOMERULAR FILTRATION RATE USING DIFFERENT FORMULAS IN TURKISH POPULATION

Year 2024, Volume: 48 Issue: 3, 826 - 834, 10.09.2024

Busra Nur Cattik , Rashida Muhammad Umar

https://doi.org/10.33483/jfpau.1458525

Abstract

Objective: Creatinine-based equations are generally used in clinical practice to estimate glomerular filtration rates (GFR), but values are not usually consistent. This study aimed to evaluate the difference between estimated GFR values using different equations.
Material and Method: Adult Turkish patients with serum creatinine measurements between January to December 2021 and complete demographic data were included. GFR values were calculated using 5 different formulas. GFR calculated with Cockcroft-Gault were normalized to body surface area and added to the comparison. Difference between GFR values and KDIGO stages were evaluated. Albunin/creatinine ratio (ACR) of patients was also assessed.
Result and Discussion: A total of 305 patients with average age of 52.92 years were included. Six different GFR calculations were recorded with median values between 51.70 to 71.77 ml/min/1.73m2. Formula of The Modification of Diet in Renal Disease with the race factor for Turkish population resulted in the lowest eGFR values. The ACR values of only 42 patients were available and it was negatively correlated to all GFR values and positively correlated to all KDIGO stages (p<0.05). There were noteworthy variations in GFR values, based on patient demographics and/or equations. The need for novel practical methods for estimating GFR in general and specific patient populations are necessary.

Keywords

Creatinine clearance, eGFR variations, GFR calculation, glomerular filtration rate, kidney function

Ethical Statement

The institutional ethics committee review board approved this study (No:2022-389) and waived consent.

Supporting Institution

-

Project Number

-

Thanks

-

TAHMİNİ GLOMERÜLER FİLTRASYON HIZININ FARKLI FORMÜLLERLE TÜRK POPÜLASYONUNDA KIYASLANMASI

Abstract

Amaç: Glomerüler filtrasyon hızlarını (GFR) tahmin etmek için klinik uygulamada genellikle kreatinin bazlı formüller kullanılır, ancak değerler genellikle tutarlı değildir. Bu çalışmanın amacı farklı formüller kullanarak eGFR değerleri arasındaki farkı değerlendirmektir.
Gereç ve Yöntem: Ocak-Aralık 2021 tarihleri arasında serum kreatinin ölçümü yapılan ve demografik verileri eksiksiz olan yetişkin Türk hastalar çalışmaya dahil edildi. GFR değerleri 5 farklı formül kullanılarak hesaplandı. Cockcroft-Gault ile hesaplanan GFR, vücut yüzey alanına göre normalize edilerek karşılaştırmaya eklendi. GFR değerleri ile KDIGO evreleri arasındaki fark değerlendirildi. Hastaların albumin/kreatinin oranı (ACR) da değerlendirmeye alındı.
Sonuç ve Tartışma: Ortalama yaşı 52.92 yıl olan toplam 305 hasta çalışmaya dahil olmuştur. Ortanca değerleri 51.70 ila 71.77 ml/dak/1.73m2 arasında değişen altı farklı GFR hesaplaması kaydedilmiştir. Türk popülasyonu için ırk kastsayısı içeren The Modification of Diet in Renal Disease formülü en düşük eGFR değerleri ile sonuçlanmıştır. Sadece 42 hastanın ACR verisi bulunmuştur ve bu değerleri tüm GFR değerleri ile negatif, tüm KDIGO evreleri ile pozitif korelasyon göstermiştir (p<0.05). Hasta demografisine ve/veya denklemlere bağlı olarak GFR değerlerinde kayda değer farklılıklar görülmüştür. Genel ve spesifik hasta popülasyonlarında GFR'yi tahmin etmek için yeni pratik yöntemlere ihtiyaç vardır.

Keywords

Böbrek fonksiyonu, eGFR varyasyonları, GFR hesaplaması, glomerüler filtrasyon hızı, kreatinin klerensi

Project Number

-

References

• 1. Bostom, A.G., Kronenberg, F., Ritz, E. (2002). Predictive performance of renal function equations for patients with chronic kidney disease and normal serum creatinine levels. Journal of the American Society of Nephrology, 13(8), 2140-2144. [CrossRef]
• 2. Erstad, B.L., Nix, D.E. (2021). Assessment of kidney function in patients with extreme obesity: A narrative review. Annals of Pharmacotherapy, 55(1), 80-88. [CrossRef]
• 3. Inker, A.L.A., Perrone, R.D. (2022). Assessment of kidney function-UpToDate Assessment of kidney function Assessment of kidney function-UpToDate. d, 1-23.
• 4. Inker, L.A., Schmid, C.H., Tighiouart, H., Eckfeldt, J.H., Feldman, H.I., Greene, T., Kusek, J.W., Manzi, J., Van Lente, F., Zhang, Y.L., Coresh, J., Levey, A.S. (2012). Estimating glomerular filtration rate from serum creatinine and cystatin C. New England Journal of Medicine, 367(1), 20-29. [CrossRef]
• 5. Cockcroft, D.W., Gault, M.H. (1976). Prediction of creatinine clearance from serum creatinine. Nephron, 16(1), 31-41. [CrossRef]
• 6. Michels, W.M., Grootendorst, D.C., Verduijn, M., Elliott, E.G., Dekker, F.W., Krediet, R.T. (2010). Performance of the Cockcroft-Gault, MDRD, and new CKD-EPI formulas in relation to GFR, age, and body size. Clinical Journal of the American Society of Nephrology, 5(6), 1003-1009. [CrossRef]
• 7. Winter, M.A., Guhr, K.N., Berg, G.M. (2012). Impact of various body weights and serum creatinine concentrations on the bias and accuracy of the Cockcroft-gault equation. Pharmacotherapy, 32(7), 604-612. [CrossRef]
• 8. Levey, A.S., Bosch, J.P., Lewis, J.B., Greene, T., Rogers, N., Roth, D. (1999). A more accurate method to estimate glomerular filtration rate from serum creatinine: A new prediction equation andrew. Annals of Internal Medicine, 130(6), 461-470. [CrossRef]
• 9. Levey, A. S., Coresh, J., Greene, T., Stevens, L. A., Zhang, Y., Hendriksen, S., Kusek, J. W., Van Lente, F. (2006). Using standardized serum creatinine values in the modification of diet in renal disease study equation for estimating glomerular filtration rate. Annals of Internal Medicine, 145(4), 247-254. [CrossRef]
• 10. Levey, A.S., Stevens, L.A., Schmid, C.H., Zhang, Y. (Lucy), Castro, A.F., Feldman, H.I., Kusek, J.W., Eggers, P., Lente, F.V., Greene, T., Coresh, J. (2009). A new equation to estimate glomerular filtration rate. Journal of Nephrology & Therapeutics, 150(09), 604-612. [CrossRef]
• 11. Inker, L.A., Eneanya, N.D., Coresh, J., Tighiouart, H., Wang, D., Sang, Y., Crews, D.C., Doria, A., Estrella, M.M., Froissart, M., Grams, M.E., Greene, T., Grubb, A., Gudnason, V., Gutiérrez, O.M., Kalil, R., Karger, A.B., Mauer, M., Navis, G., Nelson, R.G., Poggio, E.D., Rodby, R., Rossing, P., Rule, A.D., Selvin, E., Seegmiller, J.C., Shlipak, M.G., Torres, V.E., Yang, W., Ballew, S.H., Couture, S.J., Powe, N.R., Levey, A.S. (2021). New creatinine- and cystatin C-based equations to estimate GFR without race. New England Journal of Medicine, 385(19), 1737-1749. [CrossRef]
• 12. Altiparmak, M.R., Seyahi, N., Trabulus, S., Yalin, S.F., Bolayirli, M., Andican, Z.G., Suleymanlar, G., Serdengecti, K. (2013). Applicability of a different estimation equation of glomerular filtration rate in Turkey. Renal Failure, 35(8), 1116-1123. [CrossRef]
• 13. Levey, A.S., De Jong, P.E., Coresh, J., Nahas, M.E, Astor, B.C., Matsushita, K., Gansevoort, R.T., Kasiske, B. L., Eckardt, K.U. (2011). The definition, classification, and prognosis of chronic kidney disease: A KDIGO Controversies Conference report. Kidney International, 80(1), 17–28. [CrossRef]
• 14. Pierrat, A., Gravier, E., Saunders, C., Caira, M.V., Aït-Djafer, Z., Legras, B., Mallié, J.P. (2003). Predicting GFR in children and adults: A comparison of the Cockcroft-Gault, Schwartz, and Modification of Diet in Renal Disease formulas. Kidney International, 64(4), 1425-1436. [CrossRef]
• 15. Ibrahim, H., Mondress, M., Tello, A., Fan, Y., Koopmeiners, J., Thomas, W. (2005). An alternative formula to the Cockcroft-gault and the modification of diet in renal diseases formulas in predicting GFR in individuals with type 1 diabetes. Journal of the American Society of Nephrology, 16(4), 1051-1060. [CrossRef]
• 16. Hazer, B., Onder, F.O., Metli, N.B., Aslan, S.B., Yalcin, E., Akyuz, M. (2021). Accuracy of the methods used to estimate glomerular filtration rate compared to 24-hour urinary creatinine clearance in patients with chronic spinal cord injury. Journal of Spinal Cord Medicine, 46(2), 231-236. [CrossRef]
• 17. Brunetti, L., Back, H., Yu, S., Jalil, U., Kagan, L. (2021). Evaluation and enhancement of standard equations for renal function estimation in individuals with components of metabolic disease. BMC Nephrology, 22(1), 1-10. [CrossRef]
• 18. Gaspari, F., Ruggenenti, P., Porrini, E., Motterlini, N., Cannata, A., Carrara, F., Jiménez Sosa, A., Cella, C., Ferrari, S., Stucchi, N., Parvanova, A., Iliev, I., Trevisan, R., Bossi, A., Zaletel, J., Remuzzi, G. (2013). The GFR and GFR decline cannot be accurately estimated in type 2 diabetics. Kidney International, 84(1), 164-173. [CrossRef]
• 19. Demirovic, J.A., Pai, A.B., Pai, M.P. (2009). Estimation of creatinine clearance in morbidly obese patients. American Journal of Health-System Pharmacy, 66(7), 642-648. [CrossRef]
• 20. Musso, C.G., González-Torres, H. (2019). How to assess the glomerular filtration rate in the obese patient. Revista Colombiana De Nefrología, 6(2), 84-86. [CrossRef]
• 21. López-Martínez, M., Luis-Lima, S., Morales, E., Navarro-Díaz, M., Negrín-Mena, N., Folgueras, T., Escamilla, B., Estupiñán, S., Delgado-Mallén, P., Marrero-Miranda, D., González-Rinne, A., Miquel-Rodríguez, R.M., Cobo-Caso, M.A., Díaz-Martín, L., Jiménez-Sosa, A., González-Rinne, F., Torres, A., Porrini, E. (2020). The estimation of GFR and the adjustment for BSA in overweight and obesity: A dreadful combination of two errors. International Journal of Obesity, 44(5), 1129-1140. [CrossRef]
• 22. Grams, M.E., Sang, Y., Ballew, S.H., Gansevoort, R.T., Kimm, H., Kovesdy, C.P., Naimark, D., Oien, C., Smith, D.H., Coresh, J., Sarnak, M.J., Stengel, B., Tonelli, M., on behalf of the CKD Prognosis Consortium (2015). A Meta-analysis of the association of estimated GFR, albuminuria, age, race, and sex with acute kidney injury. American Journal of Kidney Diseases, 66(4), 591-601. [CrossRef]
• 23. James, M.T., Grams, M.E., Woodward, M., Elley, R., Green, J.A., Wheeler, D.C., De Jong, P., Gansevoort, R.T., Levey, A.S., Warnock, D.G., Sarnak, M.J. (2015). A meta-analysis of the association of estimated GFR, albuminuria, diabetes mellitus, and hypertension with AKI on behalf of On behalf of the CKD Prognosis Consortium. American Journal of Kidney Diseases, 66(4), 602-612. [CrossRef]